Parameter estimation of three-phase linear induction motor by a DSP-based electric-drives system

This work describes a method to characterize a three-phase linear induction motor in order to determine the various parameters used in its per-phase equivalent circuit by a DSP-based electric-drives system. In LIM (Linear Induction Motor), the air gap is very large compared with the RIMs (Rotary Induction Motors). Further, the secondary part normally does not have slotted structure. It is just made of aluminum and steel plates. Therefore, the effective air gap is larger than the physical air gap. High air gap makes a larger leakage inductance. It leads to lower efficiency and lower power factor. DC resistance test will be done to determine the value of Rs. The primary Inductance Ls will be calculated by running the LIM at synchronous speed. The secondary parameters i.e. Llr and Rr′ will be calculated by blocked-mover test. The experiment for no load test is shown and include a DC motor coupled to the LIM under test. Two methods to calculate the secondary parameters are described

Self-Commissioning of AC Motor Drives

In modern motion control and power conversion applications, the use of inverter-fed electrical machines is fast growing with continuous development in the field of power electronics and drives. The Variable Voltage Variable Frequency (VVVF) supply for electrical machines gives superior performance in terms of speed control, efficiency and dynamics compared to the machines operated directly from the mains. In one of the most basic configurations, a drive system consists of a closed loop speed control that has a current controller inside the loop. For effective and stable current control, the controller gains need to be set according to the parameters of the machine at hand. Besides, accurate parameter information is helpful in ensuring better machine exploitation as well as maintaining higher efficiency in various operating modes and conditions. The traditional methods of determining machine parameters consist of extensive machine testing under prescribed supply and ambient conditions. These methods become impracticable when the machine cannot be isolated from its load or the test equipment cannot be made available. Under such conditions, the alternatives are needed that use only the available hardware included in a standard drive to completely define the machine parameters. Self-commissioning thus comes into play in such situations. The automatic determination of machine electrical parameters before the drive is put in continuous operation is called self-commissioning of the drive system. In this thesis, self-commissioning of AC electric motors is studied, analyzed and results are presented for the implementation of different self-commissioning methods either proposed in the literature or developed in the course of this research. By far the commonest control strategy of AC machines is the vector control that allows dc machine like decoupled control of machine flux and torque. The separation of flux and torque producing current components depends heavily on the parameters of the machine at hand. In case the parameters fed to the controller do not match the actual machine parameters, the control performance deteriorates both in terms of accuracy and efficiency. For synchronous machines using permanent magnets, the magnetic model of the machine is important both for flux estimation accuracy at low speeds and for deriving maximum torque out of machine per ampere of input stator current. The identification of the magnetic model of permanent magnet synchronous machines requires special tests in a laboratory environment by loading the machine. A number of machine parameter identification methods have been studied in the past and proposed in the literature. As the power amplifier implied is almost always an inverter, the estimation of machine parameters at start-up by generating special test signals through the inverter have been researched in depth and are investigated in this thesis. These techniques are termed as offline parameter identification strategies. Other methods that focus on parameter updating during routine machine operation are called online parameter estimation methods. In this thesis, only the offline identification schemes are studied and explored further. With continuous improvements in power semiconductor devices' switching speeds and more powerful microprocessors being used for the control of electric drives, generating a host of test signals has been made possible. Analysing the machine response to the injected test signals using enhanced computational power onboard is relatively easier. These conditions favour the use of even more complex test strategies and algorithms for self-commissioning and to reduce the time required for conducting these tests. Moreover, the universal design of electric drives renders the self commissioning algorithms easily adaptable for different machine types used in industry. Among a number of AC machines available on the market, the most widely used in industrial drives are considered for study here. These include AC induction and permanent magnet synchronous machines. Induction machines still play a major part in industrial processes due, largely, to their ruggedness and maintenance-freeness; however, the permanent magnet machines are fast replacing them as competitive alternatives because of their low volume-to-power, weight-to-power ratios and higher efficiency. Their relatively light weight makes these machines a preferred choice in traction and propeller applications over their asynchronous counterpart

Predictive current control in electrical drives: an illustrated review with case examples using a five-phase induction motor drive with distributed windings

The industrial application of electric machines in variable-speed drives has grown in the last decades thanks to the development of microprocessors and power converters. Although three-phase machines constitute the most common case, the interest of the research community has been recently focused on machines with more than three phases, known as multiphase machines. The principal reason lies in the exploitation of their advantages like reliability, better current distribution among phases or lower current harmonic production in the power converter than conventional three-phase ones, to name a few. Nevertheless, multiphase drives applications require the development of complex controllers to regulate the torque (or speed) and flux of the machine. In this regard, predictive current controllers have recently appeared as a viable alternative due to an easy formulation and a high flexibility to incorporate different control objectives. It is found however that these controllers face some peculiarities and limitations in their use that require attention. This work attempts to tackle the predictive current control technique as a viable alternative for the regulation of multiphase drives, paying special attention to the development of the control technique and the discussion of the benefits and limitations. Case examples with experimental results in a symmetrical five-phase induction machine with distributed windings in motoring mode of operation are used to this end

FEAfix: FEA Refinement of Design Equations for Synchronous Reluctance Machines

The Synchronous Reluctance (SyR) machine is an attractive substitute of induction motors and synchronous PM motors thanks to its high efficiency and low cost of manufacturing. Yet, its design cannot be considered a mature topic, especially for what concerns the rotor geometry. Design equations were proposed for SyR machines by different authors, representing a good starting point and a useful guideline for designers, but they are far from giving accurate results. Conversely, the design procedures based on finite element analysis tend to rely on the brute force of optimization algorithms rather than on the designer’s insight. In this work, a comprehensive design procedure is proposed, where design equations are complemented by the use of the iron saturation curve and the new fast FEA approach named FEAfix. This corrects the equations results via few static FEA simulations per design plane, i.e. per family of machines, rather then by FEA simulating the single machine under design. The general conclusion is drawn that the considered analytical model alone tend to overestimate torque by as much as 40% (average on the design plane). Upon augmenting equations with the saturation curve, the average overestimate drops in the vicinity of 10% error. Finally, the proposed FEAfix refinement guarantees 2% to 1% torque evaluation error, depending on the admitted computational time. High precision is therefore obtained while retaining the generality of the analytical approach